Late Breaking Abstract - Muscle Oxygenation Kinetics Are Impaired in Long COVID: A Case-Control Study Using NIRS
Bibliographic record
Abstract
Objective: to evaluate the kinetics of oxyhemoglobin (oxy-[Hb/Mb]) and deoxyhemoglobin (deoxy-[Hb/Mb]) in individuals with Post-Acute Sequelae of SARS-CoV-2 infection (PASC), compared to a control group. Methods: This observational case-control study included individuals with PASC (n=30) and a matched control group (n=10) who had tested positive for COVID-19 but were either asymptomatic. Participants underwent constant-load exercise tests, with near-infrared spectroscopy (NIRS) used to measure oxy- and deoxy-[Hb/Mb] kinetics in the vastus lateralis muscle. Results: The most prevalent comorbidities among long COVID patients were hypertension (70%) and obesity (43%). All participants receiving at least two doses of a COVID-19 vaccine. Our findings revealed that individuals with long COVID exhibited significantly slower mean response time (MRT) in both oxy-[Hb/Mb] and deoxy-[Hb/Mb] kinetics compared to controls (p<0.05). Body adiposity was correlated with both oxy-[Hb/Mb] τ (r=0.488) and MRT (r=0.431). Multivariate regression analysis demonstrated that BMI was the primary factor influencing delayed τ (β = 5.8; 95% CI: 1.3 to 10.3; p = 0.012) and MRT (β = 7.6; 95% CI: 1.1 to 14.1; p = 0.023) of oxy-[Hb/Mb]. Obesity was also identified as a significant independent predictor of these kinetic impairments, irrespective of sex or COVID-19 severity, and had notably slowered τ and MRT responses (p<0.001). Conclusion: This study identified significant impairments in muscle oxygenation and cardiorespiratory kinetics during exercise in individuals with PASC, particularly those with comorbid obesity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".